Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You manage a Microsoft Fabric Eventstream that ingests JSON telemetry from Azure Event Hubs into a Lakehouse delta table. Ingestion has stopped, and the monitoring page shows a rising Dropped events - Invalid JSON count. You must quickly learn what is wrong with the incoming messages without stopping the stream. What should you do first?
Enable debug mode for the Eventstream to capture and inspect sample dropped events in the monitoring pane.
Spin up an Azure Stream Analytics job that writes all Event Hubs messages to a staging blob container for later inspection.
Create a system filter in the Eventstream that discards events with any null field values.
Scale up the Event Hubs namespace by adding more throughput units to eliminate backpressure.
Creating an Azure Stream Analytics job that continuously copies all Event Hubs messages to a staging Azure Blob Storage container lets you inspect the raw payloads immediately and at scale. Because the job captures every event with minimal additional latency, you can open the blobs, find malformed records, and spot pattern errors without pausing the running Eventstream. Eventstream itself has no live debug view that surfaces dropped-event samples, and increasing Event Hubs throughput or adding a filter would not reveal the problematic JSON.
Ask Bash
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What is Azure Stream Analytics, and how does it support troubleshooting in this scenario?
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Why is enabling debug mode in the Eventstream not a suitable solution?
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What are some common causes of 'Dropped events - Invalid JSON' in Azure Event Hubs?
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Microsoft Fabric Data Engineer Associate DP-700
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